Mixtral 8x7B on Apple M3 Max · 36GB

🐢 CPU-only (slow) — Mixtral 8x7B @ Q4_K_M
Mixtral 8x7B 8x7B (MoE) at Q4_K_M needs ~28.7 GB (weights 26.4 GB + KV 1.0 GB + overhead 1.3 GB @ 8K ctx) of your 21.1 GB usable (of 36.0 GB unified memory) — runs on CPU only. Expect ~3–4 tok/s (slow).
context @ Q4_K_M: runs to its full 32K
quantneedsspeed
✗ Q8_049.5 GB—
✗ Q5_K_M33.5 GB—
~ Q4_K_M28.7 GB~3–4 tok/s (slow)
~ Q3_K_M23.3 GB~3–5 tok/s (slow)
$runlocal install mixtral:8x7b
runlocal verdict card
download card share on x share on reddit drop it in your model-drop post
Mixtral 8x7B: CPU-only (slow)
for your own README — links back here

Same model, other machines: Apple M1 · Apple M1 Pro · Apple M2 · Apple M3 Pro · Apple M2 Pro · Apple M4 Pro

Also runs on a Apple M3 Max: Qwen3 · DeepSeek-R1 (distill) · Qwen2.5 · Gemma 4 · Gemma 3

Best models for a Apple M3 Max · 36GB →

Architecturally similar

These share Mixtral 8x7B's KV-cache geometry — they size memory the same way, so here's how they fit on a Apple M3 Max · 36GB too:

modelsharesverdict here
Llama 3.1 8kv/128hd ✅ Runs comfortably
Qwen2.5-Coder 8kv/128hd ✅ Runs (tight)
Llama 3.2 8kv/128hd ✅ Runs comfortably
Llama 3.3 8kv/128hd 🐢 CPU-only (slow)
Mistral 7B 8kv/128hd ✅ Runs comfortably
Mistral Small 3 8kv/128hd ✅ Runs (tight)
Mistral Nemo 8kv/128hd ✅ Runs comfortably
Codestral 8kv/128hd ✅ Runs (tight)

…and 8 more — see the Mixtral 8x7B page.

Check any combo yourself: open the checker →